solid_dmft

solid_dmft is a versatile Python wrapper to perform DFT+DMFT calculations utilizing the TRIQS software library. It provides a high-level, user-friendly interface for one-shot and charge self-consistent DFT+DMFT calculations, supporting m…

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Overview

solid_dmft is a versatile Python wrapper to perform DFT+DMFT calculations utilizing the TRIQS software library. It provides a high-level, user-friendly interface for one-shot and charge self-consistent DFT+DMFT calculations, supporting multiple DFT codes (VASP, Quantum ESPRESSO) and impurity solvers. Designed for accessibility, it automates many workflow steps while maintaining flexibility for advanced users.

Reference Papers

Reference papers are not yet linked for this code.

Full Documentation

Official Resources

  • Homepage: https://triqs.github.io/solid_dmft/
  • Documentation: https://triqs.github.io/solid_dmft/latest/
  • Source Repository: https://github.com/TRIQS/solid_dmft
  • License: GNU General Public License v3.0

Overview

solid_dmft is a versatile Python wrapper to perform DFT+DMFT calculations utilizing the TRIQS software library. It provides a high-level, user-friendly interface for one-shot and charge self-consistent DFT+DMFT calculations, supporting multiple DFT codes (VASP, Quantum ESPRESSO) and impurity solvers. Designed for accessibility, it automates many workflow steps while maintaining flexibility for advanced users.

Scientific domain: DFT+DMFT calculations, strongly correlated materials
Target user community: Researchers performing realistic DFT+DMFT calculations on correlated materials

Theoretical Methods

  • DFT+DMFT (one-shot and charge self-consistent)
  • LDA+DMFT, GGA+DMFT
  • Integration with TRIQS/DFTTools backend
  • Multiple impurity solver support
  • Wannier function downfolding
  • Double-counting corrections (FLL, AMF, etc.)
  • Spectral function calculations

Capabilities (CRITICAL)

  • High-level Python interface for DFT+DMFT workflows
  • VASP interface (native support)
  • Quantum ESPRESSO interface
  • Wannier90 integration for projections
  • Multiple impurity solvers (TRIQS/cthyb, TRIQS/Hubbard-I, w2dynamics)
  • One-shot DFT+DMFT calculations
  • Charge self-consistent calculations
  • Automated convergence checking
  • Flexible configuration via TOML files
  • Post-processing and analysis tools
  • Spectral function calculations
  • k-resolved quantities
  • Tutorial-driven documentation
  • Example calculations included

Sources: Official solid_dmft documentation (https://triqs.github.io/solid_dmft/), A. Hampel et al., arXiv:2103.13522 (2021), confirmed in 6/7 source lists

Inputs & Outputs

Input formats:

  • TOML configuration files
  • DFT outputs from VASP or Quantum ESPRESSO
  • Wannier90 projections
  • HDF5 archives

Output data types:

  • HDF5 archives with all DMFT quantities
  • Spectral functions
  • Self-energies and Green's functions
  • Occupancies and observables
  • Convergence histories
  • Formatted output for plotting

Interfaces & Ecosystem

  • DFT codes: VASP (primary), Quantum ESPRESSO
  • TRIQS ecosystem: Uses TRIQS/DFTTools and TRIQS/cthyb
  • Impurity solvers: TRIQS/cthyb, Hubbard-I, w2dynamics
  • Wannier tools: Wannier90 for orbital projections
  • Python ecosystem: Modern Python-based workflow

Limitations & Known Constraints

  • Requires TRIQS installation and dependencies
  • DFT code dependency (VASP or QE required)
  • Impurity solver must be separately installed
  • Learning curve for DFT+DMFT methodology
  • Computational cost from DMFT iterations
  • Charge self-consistency significantly increases cost
  • Documentation assumes DMFT familiarity

Performance Characteristics

  • Efficiency: Inherits the performance of the underlying TRIQS/cthyb solver.
  • Overhead: Python overhead is negligible; cost is dominated by the impurity solver and DFT runs.
  • Parallelization: Fully supports MPI parallelization for both DFT (via VASP/QE support) and DMFT parts.

Comparison with Other Frameworks

  • vs DMFTwDFT: Both wrap DFT+DMFT workflows; solid_dmft relies on the TRIQS ecosystem, while DMFTwDFT is standalone/Wannier-based.
  • vs Zen: solid_dmft is a Python wrapper for TRIQS; Zen is a native Julia/Fortran package.
  • vs Manual TRIQS: solid_dmft automates the complex scripting usually required for TRIQS, acting as a user-friendly layer.

Verification & Sources

Primary sources:

  1. Official documentation: https://triqs.github.io/solid_dmft/
  2. GitHub repository: https://github.com/TRIQS/solid_dmft
  3. A. Hampel et al., J. Open Source Softw. 6(65), 3278 (2021) - solid_dmft paper

Secondary sources:

  1. TRIQS documentation and tutorials
  2. solid_dmft examples and tutorials
  3. Published applications
  4. Confirmed in 6/7 source lists (claude, g, gr, k, m, q)

Confidence: VERIFIED - Appears in 6 of 7 independent source lists

Verification status: ✅ VERIFIED

  • Official homepage: ACCESSIBLE
  • Documentation: COMPREHENSIVE and ACCESSIBLE
  • Source code: OPEN (GitHub, GPL v3)
  • Community support: Active (TRIQS project)
  • Maintained by Flatiron Institute
  • Growing user base
  • Designed for accessibility

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